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Welcome to Schools Count!

Schools Count, in the first semester, will teach you the
statistical skills to answer the following questions for your school:

Measuring Academic-Achievement Gaps (Racial, SPED and Socieconomic): Where are the gaps, and are they growing or shrinking?

Identifying At-Risk Students: What are the educational risk factors, and how do we detect them early so we can intervene early?

Analyzing Pattern Breakers: Who are the students succeeding despite risk factors, and what can we learn from their success?

Schools Count Mission: For every school, a data team.
For every data team, a diverse group of educators (including special educators,
physical educators and art educators) who have the skills and knowledge to answer their most
pressing educational questions about teaching and learning in their school
using their school's quantitave data.

Schools Count is <<UNDER
CONSTRUCTION>>. The
site should be fully functional by September, 2013. "Fully
functional" means that a school data team with no
data-analytic experience can begin analyzing its own data
in the first week, Unit 1, and continue progressing one
unit per week through the Intermediate Semester. In the
meantime, feel free to check out anything and everything.

Getting Started (3 Steps)

Watch the Unit 1 lecture, here. The Unit 1 lecture
is the longest of all, clocking in at 211 minutes. (The
Unit 2 lecture is more typical at 97 minutes.) I never
said that this course would be easy! Good teachers say
to their students, "This is easy. You can do it." The
best teachers say to their students, "This is hard. You
can do it." I'm working to be the best teacher I can be,
as are you. This is hard. You can do it.

Obtain a dataset, which can be from a database,
spreadsheet or gradebook from your school. The dataset
should be structured like a gradebook in that it has one
row per student. The first few columns are for IDs
and/or names. Then, there are columns for things such as
scores, grades, sex, race/ethnicity, effort, conduct,
attendance or anything really. Save the dataset in .csv
format (comma-separated value format), which is a very
simple format standard across platforms. One way to save
a dataset in .csv format is to open up the dataset in
common spreadsheet software (e.g., Microsoft eXcel), and
use the "Save as..." menu. (If you cannot obtain a
dataset, you can use a provided dataset, but then your
work products will be academic exercises instead of
-practical resources for your school.)

Note that you do not have to take the entire four-semester
course to learn a heck of a lot. The first semester alone is
a complete introduction to educational data analysis. The
first two units alone are a complete introduction to
exploratory data analysis.